DOI

Domain-specific languages (DSLs) have extensively been investigated in research and have frequently been applied in practice for over 20 years. While DSLs have been attributed improvements in terms of productivity, maintainability, and taming accidental complexity, surprisingly, we know little about their actual impact on the software engineering practice. This PhD project, that is done in close collaboration with our industrial partner Océ - A Canon Company, offers a unique opportunity to study the application of DSLs using a longitudinal field study. In particular, we focus on introducing DSLs with language workbenches, i.e., infrastructures for designing and deploying DSLs, for projects that are already running for several years and for which extensive domain analysis outcomes are available. In doing so, we expect to gain a novel perspective on DSLs in practice. Additionally, we aim to derive best practices for DSL development and to identify and overcome limitations in the current state-of-the-art tooling for DSLs.

Original languageEnglish
Title of host publicationESEC/FSE 2019
Subtitle of host publicationProceedings of the 2019 27th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering
EditorsSven Apel, Marlon Dumas, Alessandra Russo, Dietmar Pfahl
Place of PublicationNew York
PublisherAssociation for Computing Machinery (ACM)
Pages1152-1155
Number of pages4
ISBN (Print)978-1-4503-5572-8
DOIs
Publication statusPublished - 12 Aug 2019
Event27th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ESEC/FSE 2019: The 27th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering - Tallinn, Estonia
Duration: 26 Aug 201930 Aug 2019

Conference

Conference27th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ESEC/FSE 2019
CountryEstonia
CityTallinn
Period26/08/1930/08/19

    Research areas

  • Domain-specific languages, Language workbenches, Longitudinal field study, Model-driven engineering

ID: 57453602